We present an open source, freely available Java implementation of Align, Disambiguate, and Walk (ADW), a state-of-the-art approach for measuring semantic similarity based on the Personalized PageRank algorithm. A pair of linguistic items, such as phrases or sentences, are first disambiguated using an alignment-based disambiguation technique and then modeled using random walks on the WordNet graph. ADW provides three main advantages: (1) it is applicable to all types of linguistic items, from word senses to texts; (2) it is all-in-one, i.e., it does not need any additional resource, training or tuning; and (3) it has proven to be highly reliable at different lexical levels and multiple evaluation benchmarks. We are releasing the source code at https://github.com/pilehvar/adw/. We also provide at http://lcl.uniroma1.it/adw/ a Web interface and a Java API that can be seamlessly integrated into other NLP systems requiring semantic similarity measurement.
CITATION STYLE
Pilehvar, M. T., & Navigli, R. (2015). An open-source framework for multi-level semantic similarity measurement. In NAACL-HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Demonstrations, Proceedings (pp. 76–80). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/n15-3016
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